Several pictures, one AI video: how we send @Image1…@Image7 to Kling (and six other models) in order

Описание и применение

Компонент RefVid теперь позволяет добавлять до семи изображений, автоматически назначать им теги @ImageN и переводить эти теги в формат, понятный каждому из восьми моделей, обеспечивая последовательное воспроизведение изображений в видео.

Задача

Animating multiple distinct images in a single AI‑generated video while preserving each image’s identity and context across shots.

Результат

The composer now handles up to seven images per clip, automatically translates tags for each model, enforces per‑model limits before charging, and produces consistent multi‑shot videos.

Рабочий процесс

• 1. Drag or paste images into the composer; each receives a sequential @ImageN tag immediately.
• 2. Compose shots, inserting tags in prompts (e.g., "@Image1").
• 3. On render, the system orders images per model, computes final positions, and rewrites tags to the model’s required syntax.
• 4. The API call includes image_urls and elements; the model generates the video.
• 5. The studio displays the resulting clip and prompts for review.

Доказательства

Every image you add becomes a tag, @Image1, @Image2, and a shot's text says which one it is about.

Источник

The system rewrites every @ImageN token into that model's own name for that position.

Источник

On the list models, when a clip is close to the cap, extra angles of a saved subject go first; a picture or a start frame never does.

Источник